def plot_thick_vs_eff_meta(self):
"""plots the efficiency function for a set of thicknesses,
Args:
sigma: Full sigma calculation fo the detector
ranges: Ranges calculation
blades: detector blades
result: Efficiency
figure: figure to plot in
Returns:
plotted figure
reference: figure 3.12 On Francesco's Thesis
"""
sigma = self.calculate_sigma()
sigmalist = []
c = 0
for s in sigma:
sigmalist.append([s, self.wavelength[c][1]])
c += 1
ranges = self.calculate_ranges()
blades = self.blades
result = self.calculate_eff()
if self.single:
thickVsEff = efftools.metadata_samethick_vs_thickandnb_single(sigmalist, ranges, len(blades))
else:
thickVsEff = efftools.metadata_samethick_vs_thickandnb(sigmalist, ranges, len(blades))
self.metadata.update({'thickVsEff': thickVsEff})
def plot_thick_vs_eff_meta(self, sigma, ranges, blades, result, figure):
"""plots the efficiency function for a set of thicknesses,
Args:
sigma: Full sigma calculation fo the detector
ranges: Ranges calculation
blades: detector blades
result: Efficiency
figure: figure to plot in
Returns:
plotted figure
reference: figure 3.12 On Francesco's Thesis
"""
bx = figure.add_subplot(111)
sigmalist = []
c = 0
for s in sigma:
sigmalist.append([s, self.wavelength[c][1]])
c += 1
if self.single:
#TODO Poli sigma
thickVsEff = efftools.metadata_samethick_vs_thickandnb_single(sigmalist, ranges, len(blades))
bx.plot(thickVsEff[0], np.array(thickVsEff[1]), label=" Backscatering")
bx.plot(thickVsEff[0], np.array(thickVsEff[2]), label=" Transmission")
bx.legend(numpoints=1)
bx.grid(True)
bx.set_xlabel('Converter thickness ($\mu$m)')
bx.set_ylabel('Detector efficiency (%)')
# line = bx.plot([self.blades[0].backscatter, self.blades[0].backscatter],
# [0, result[1][0] * 100], '--')
# plt.setp(line, 'color', 'k', 'linewidth', 0.5)
else:
thickVsEff = efftools.metadata_samethick_vs_thickandnb(sigmalist, ranges, len(blades))
self.metadata.update({'thickVsEff': thickVsEff})
bx.plot(thickVsEff[0],np.array(thickVsEff[1]))
bx.grid(True)
bx.set_xlabel('Converter thickness ($\mu$m)')
bx.set_ylabel('Detector efficiency (%)')
line = bx.plot([self.blades[0].backscatter, self.blades[0].backscatter], [0, result[1]],
'--')
plt.setp(line, 'color', 'r', 'linewidth', 0.5)
if self.single:
line2 = bx.plot([0, self.blades[0].backscatter], [result[1][0], result[1][0]], '--')
line3 = bx.plot([0, self.blades[0].backscatter], [result[0][0], result[0][0]], '--')
line4 = bx.plot([self.blades[0].backscatter, self.blades[0].backscatter], [result[0][0], 0], '--')
line5 = bx.plot([self.blades[0].backscatter, self.blades[0].backscatter], [result[1][0], 0], '--')
plt.setp(line3, 'color', 'r', 'linewidth', 0.5)
plt.setp(line4, 'color', 'r', 'linewidth', 0.5)
plt.setp(line5, 'color', 'r', 'linewidth', 0.5)
else:
line2 = bx.plot([0, np.array(self.blades[0].backscatter)], [result[1], result[1]], '--')
plt.setp(line2, 'color', 'r', 'linewidth', 0.5)
# ticks = bx.get_yticks() * 100
# bx.set_yticklabels(ticks)
return bx
def plot_thick_vs_eff2(self):
"""plots the efficiency function for a set of thicknesses,
Args:
sigma: Full sigma calculation fo the detector
ranges: Ranges calculation
blades: detector blades
result: Efficiency
figure: figure to plot in
Returns:
plotted figure
reference: figure 3.12 On Francesco's Thesis
"""
sigma = self.calculate_sigma()
sigmalist = []
c = 0
for s in sigma:
sigmalist.append([s, self.wavelength[c][1]])
c += 1
ranges = self.calculate_ranges()
blades = self.blades
result = self.calculate_eff()
bx = plt.figure(1)
plt.subplot(111)
if self.single:
thickVsEff = efftools.metadata_samethick_vs_thickandnb_single(sigmalist, ranges, len(blades))
plt.plot(thickVsEff[0], np.array(thickVsEff[1]), label=" Backscattering")
plt.plot(thickVsEff[0], np.array(thickVsEff[2]), label=" Transmission")
plt.plot(thickVsEff[0], np.array(thickVsEff[3]), label=" Total")
self.metadata.update({'thickVsEffBack': [thickVsEff[0], np.array(thickVsEff[1])]})
self.metadata.update({'thickVsEffTrans': [thickVsEff[0], np.array(thickVsEff[2])]})
plt.legend(numpoints=1)
plt.grid(True)
meta = self.metadata.get('thickVsEffBack')
meta2 = self.metadata.get('thickVsEffTrans')
data = np.array([meta[0], meta[1]])
data2 = np.array([meta2[0], meta2[1]])
'''
datafile_id = open('/Users/alvarocbasanez/backscattering', 'w+')
datafile_id2 = open('/Users/alvarocbasanez/transmission', 'w+')
for a, am in zip(data[0], data[1]):
datafile_id.write("{}\t{}\n".format(a, am))
for a, am in zip(data2[0], data2[1]):
datafile_id2.write("{}\t{}\n".format(a, am))
datafile_id.close()
datafile_id2.close()
'''
plt.xlabel(r'Converter thickness ($\mu$m)')
plt.ylabel('Detector efficiency (%)')
line = plt.plot([self.blades[0].backscatter, self.blades[0].backscatter],[0, result[1] ], '--')
plt.setp(line, 'color', 'k', 'linewidth', 0.5)
else:
thickVsEff = efftools.metadata_samethick_vs_thickandnb(sigmalist, ranges, len(blades))
self.metadata.update({'thickVsEff': thickVsEff})
plt.plot(thickVsEff[0], np.array(thickVsEff[1]))
plt.grid(True)
plt.xlabel(r'Converter thickness ($\mu$m)')
plt.ylabel('Detector efficiency (%)')
line = plt.plot([self.blades[0].backscatter, self.blades[0].backscatter], [0, np.array(result[1])],'--')
plt.setp(line, 'color', 'k', 'linewidth', 0.5)
if self.single:
print()
#line2 = plt.plot([0, self.blades[0].backscatter], [result[0][1], result[0][1]], '--')
else:
line2 = plt.plot([0, self.blades[0].backscatter], [np.array(result[1]), np.array(result[1])], '--')
plt.setp(line2, 'color', 'k', 'linewidth', 0.5)
return bx